How can GenAI be used in the real world? Who are the potential winners? In a major cross-sector report (available for clients only), BNP Paribas Exane has brought together more than 30 top-ranked analysts to cut through the noise and assess the real opportunities behind the hype.
GenAI, behind the hype… Is it really different this time?
Certainly, there’s been no lack of attention and buzz around GenAI since the launch of ChatGPT in November 2022. But investors have lived through numerous tech hype cycles before, most recently with blockchain and the metaverse. Will this time really be any different? BNP Paribas Exane analysts think so.
While GenAI hype will eventually fade, the team believes the potential is real given the tangible benefits in applications already in use today, or planned for launch by year end, including Microsoft 365 Copilot, Adobe Firefly and Salesforce’s EinsteinGPT.
- Traditional AI uses algorithms, which have been trained on historical data, to make predictions about future outcomes.
- Generative AI, on the other hand, goes beyond traditional AI by leveraging deep learning and neural networks to create original content, also based on model training using historical data. It can generate new text, images, video, music, software code, exhibiting a level of creativity.
- GenAI can create something ‘new’ while traditional AI is focused on identifying patterns in order to solve specific tasks.
What should investors and corporates consider when looking at GenAI opportunities?
With applications ranging from the obvious – such as chatbots, image creation and education – to the less obvious – such as discriminatory pricing, cyber-security and medical imaging – the challenge for investors and corporates alike now is to understand the multi-faceted risks and opportunities that GenAI presents. And while the potential of GenAI will naturally vary hugely between industries, none are left unaffected in analysts’ view, given the need for administrative and support tasks in even the most industrialised companies.
Generative AI will impact all industries, but will affect them very differently. Some companies will launch new products and services while others will be able to more efficiently communicate with, sell to, and service customers.
Stefan Slowinski, Global Head of Software Research, BNP Paribas Exane
BNP Paribas Exane’s sector teams explored how GenAI can be used to improve or disrupt their industries, and what this means for their stock coverage in a report. The analysts found key phrases related to GenAI across sectors, ‘productivity’ and ‘efficiency’ being clearly top of mind, but revenue and pricing opportunities were also part of the mix.
Regulation is clearly recognised as an impediment to GenAI usage, but data privacy and union opposition to the job cuts potentially implied by productivity gains arguably deserve more airtime.
Creative disruption: Who wins?
Outside of the technology sector, BNP Paribas Exane teams see the greatest potential impact in consumer facing sectors. In media, the risk of disruption is high within music, but there seem to be more opportunity than risk in video games. In retail, the report shows that there could be greater opportunity for personalised marketing and discriminatory pricing, even if retaining gains may be tough. And in business services, analysts opportunity for credit bureaux, but disruption to the staffing agency business model.
As for basic material and industrial names, GenAI is likely to be more of another step on the digital journey, rather than revolutionary in itself.
A productivity super-cycle ahead?
What virtually all sectors have in common though, is the potential for GenAI driven productivity gains, even if this is limited to back office and support functions. With this in mind, and given the experience of the US in the 1990s, BNP Paribas Exane’s economists estimate that the diffusion of AI in most advanced economies could boost productivity by around 1% p.a.
The strategists also home in on this theme, suggesting that GenAI could increase productivity without increasing pressures from labour costs and potentially even bring forward a productivity super-cycle. This could keep the wage share of profit low relative to productivity and lead to higher profit margins – and valuations – over a multi-year period.
While all sectors should see productivity gains, those such as software, with high labour costs AND a high proportion of worktime addressable to GenAI productivity gains offer the greatest potential.
Stuart Pearson, Head of thematic research at BNP Paribas Exane
GenAI through an ESG lens: risks to consider
AI has the capacity for tremendous good, with some claiming it can help cure cancer and solve climate change. But there are also significant risks from reinforcing discrimination to undermining democracy, and even, at the most extreme end of predictions, ending human existence. Governments are scrambling to catch-up to balance innovation vs safety. BNP Paribas Exane’s analysts believe there is significant risk of a misalignment between short-term financial incentives and the long-term interests of humanity, and as such AI should be a major focus for ESG investors.
Although BNP Paribas Exane analysts believe that generative AI’s hype will fade, the impacts is expected to be substantial but will vary between industries – some benefitting more than others. However, they agree that all sectors will profit from an increase in productivity with a potential gain in profit margins. GenAI’s potential is undeniable but BNP Paribas Exane teams are conscious that risks can arise, especially from an ESG point of view.